Top 13
Prep plan
Updated weekly · Last refresh Aug 30

Aviva Machine Learning Engineer Interview Questions

The questions to prepare for a Aviva Machine Learning Engineer interview. Questions from real interview reports rank first. Updated weekly.

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1
CodingStart here. 3 questions · ~25 min
Optimizing Time and Space ComplexityEasy

Explain how to improve coding solutions by reducing time complexity first, then balancing space trade-offs.

Hash TablesArraysGreedyAviva
Modular, Reusable CodeMedium

Tests your software design practices for collaboration and long-term maintainability.

Aviva
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2
Machine Learning4 questions · ~33 min
Bagging vs Boosting ExplainedMedium

Explain how bagging and boosting differ, and identify a representative algorithm for each ensemble method.

Ensemble Methodsmodel trainingSupervised LearningAviva
Feature Engineering for Sparse DataMedium

Explain how to engineer features for high-dimensional sparse data while controlling overfitting, dimensionality, and training cost.

data preprocessingFeature Engineeringsparse datasetsAviva
Handling Class ImbalanceMedium

Tests your ability to address skewed data and improve model performance on minority classes.

data preprocessingClass ImbalanceAviva
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3
Behavioral & Leadership3 questions · ~25 min
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4
More topics3 questions · ~25 min
Design a Low Latency Inference PlatformHard

Design a low latency ML inference platform for high-frequency online predictions with strict response times and evolving model features.

high-frequency requestslatencysystem architectureAviva
Metrics for Insurance ClaimsMedium

Tests your ability to choose appropriate evaluation metrics aligned to business outcomes and risk.

performance metricsModel EvaluationAviva
Design Feature Drift Monitoring SystemHard

Design a production ranking system with robust feature drift monitoring across batch and real-time features at high QPS.

Feature StoreFeature DriftModel ServingAviva
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